ABSTRACT
Nanophotonics, and more specifically plasmonics, provides a rich toolbox for biomolecular sensing, since the engineered metasurfaces can enhance light-matter interactions to unprecedented levels. So far, biosensing associated with high-quality factor plasmonic resonances has almost exclusively relied on detection of spectral shifts and their associated intensity changes. However, the phase response of the plasmonic resonances have rarely been exploited, mainly because this requires a more sophisticated optical arrangement. Here we present a new phase-sensitive platform for high-throughput and label-free biosensing enhanced by plasmonics. It employs specifically designed Au nanohole arrays and a large field-of-view interferometric lens-free imaging reader operating in a collinear optical path configuration. This unique combination allows the detection of atomically thin (angstrom-level) topographical features over large areas, enabling simultaneous reading of thousands of microarray elements. As the plasmonic chips are fabricated using scalable techniques and the imaging reader is built with low-cost off-the-shelf consumer electronic and optical components, the proposed platform is ideal for point-of-care ultrasensitive biomarker detection from small sample volumes. Our research opens new horizons for on-site disease diagnostics and remote health monitoring.
ABSTRACT
Proteolytic signaling, or regulated proteolysis, is an essential part of many important pathways such as Notch, Wnt, and Hedgehog. How the structure of the cleaved substrate regions influences the efficacy of proteolytic processing remains underexplored. Here, we analyzed the relative importance in proteolysis of various structural features derived from substrate sequences using a dataset of more than 5000 experimentally verified proteolytic events captured in CutDB. Accessibility to the solvent was recognized as an essential property of a proteolytically processed polypeptide chain. Proteolytic events were found nearly uniformly distributed among three types of secondary structure, although with some enrichment in loops. Cleavages in α-helices were found to be relatively abundant in regions apparently prone to unfolding, while cleavages in ß-structures tended to be located at the periphery of ß-sheets. Application of the same statistical procedures to proteolytic events divided into separate sets according to the catalytic classes of proteases proved consistency of the results and confirmed that the structural mechanisms of proteolysis are universal. The estimated prediction power of sequence-derived structural features, which turned out to be sufficiently high, presents a rationale for their use in bioinformatic prediction of proteolytic events.
